Some may know and choose to ignore the fact, but every single thing you do online is being tracked and guess what? For better or for worse it is there forever. Whether you're simply browsing websites or you are accessing confidential information that you would rather no one know about there are ways to remain anonymous. Imagine this scenario, you create an account on a forum with your name and decide to do some political freedom fighting with it. Years down the road a future employer of yours does a simple google search of your name and finds everything you've ever done. They don't hire you. This is a very simple scenario that just scratches the surface of reasons to stay anonymous but the point remains the same. Knowing when and how to remain anonymous is very important. Many people already realize this but have no clue where to start. This book has step by step instructions and techniques involving Tor, VPN's, Proxies, and more that will take you to the deepest levels of anonymity in which not even the all seeing NSA will be able to track you. Bonus download included in the book! (Step-by-step guide to setup TOR) A Preview of What You Will Learn ✔ How to Remain COMPLETELY Anonymous ✔ Exactly What Tor, VPN's, and PGP Are. ✔ How To Setup and Use Tor Correctly For Maximum Safety ✔ Key Mistakes To Avoid ✔ The Real Capabilities of The NSA ✔ Much, much more! Take back your privacy today. Scroll up and buy this book!

    

    Building on the successful top-down approach of previous editions, this fourth edition continues with an early emphasis on application-layer paradigms and application programming interfaces, encouraging a hands-on experience with protocols and networking concepts.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    This guide, which can be used with any text or can stand alone, contains at the beginning of each chapter a list of key definitions, a summary of major concepts, step by step solutions to dozens of problems, and additional practice problems.

    Craftsm- ship has its quiet rewards, the satisfaction that comes from building a useful object and making it work. Excitement arrives with the ?ash of insight that cracks a previously intractable problem. The spiritual quest for elegance can turn the hacker into an artist. Therearepleasuresinparsimony, insqueezingthelastdropofperformanceoutofclever algorithms and tight coding. Thegames, puzzles, andchallengesofproblemsfrominternationalprogrammingc- petitionsareagreatwaytoexperiencethesepleasureswhileimprovingyouralgorithmic and coding skills. This book contains over 100 problems that have appeared in previous programming contests, along with discussions of the theory and ideas necessary to - tack them. Instant online grading for all of these problems is available from two WWW robot judging sites. Combining this book with a judge gives an exciting new way to challenge and improve your programming skills. This book can be used for self-study, for teaching innovative courses in algorithms and programming, and in training for international competition. To the Reader Theproblemsinthisbookhavebeenselectedfromover1,000programmingproblemsat the Universidad de Valladolid online judge, available athttp: //online-judge.uva.es.The judgehasruledonwelloveronemillionsubmissionsfrom27,000registeredusersaround the world to date. We have taken only the best of the best, the most fun, exciting, and interesting problems availa

    This book offers concrete examples and exercises in the dynamic and versatile Python language to demonstrate and reinforce these concepts. Learn the basic tools to start writing the programs that interest you, and get a better understanding of what software can (and cannot) do. When you're finished, you'll have the necessary foundation to learn any programming language or tackle any software project you choose. With a focus on programming concepts, this book teaches you how to:Understand the core features of all programming languages, including: variables, statements, decisions, loops, expressions, and operatorsReuse code with functionsUse library code to save time and effortSelect the best data structure to manage complex dataWrite programs that talk to the WebShare your data with other programsWrite programs that test themselves and help you avoid embarrassing coding errors.Contents Intro xxiii1 Starting to Code: Finding Your Way2 Textual Data: Every String Has Its Place3 Functions: Let’s Get Organized4 Data Files and Arrays: Sort It Out5 Hashes and Databases: Putting Data in Its Place6 Modular Programming: Keeping Things Straight7 Building a Graphical User Interface: Going All Gooey8 GUIs and Data: Data Entry Widgets8 1/2 Exceptions and Message Boxes: Get the Message? 9 Graphical Interface Elements: Selecting the Right Tool10 Custom Widgets and Classes: With an Object in MindAppendix i Leftovers: The Top Ten Things (We Didn’t Cover)

    Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

    In How the Internet Happened, he chronicles the whole fascinating story for the first time, beginning in a dusty Illinois basement in 1993, when a group of college kids set off a once-in-an-epoch revolution with what would become the first “dotcom.”Depicting the lives of now-famous innovators like Netscape’s Marc Andreessen and Facebook’s Mark Zuckerberg, McCullough also reveals surprising quirks and unknown tales as he tracks both the technology and the culture around the internet’s rise. Cinematic in detail and unprecedented in scope, the result both enlightens and informs as it draws back the curtain on the new rhythm of disruption and innovation the internet fostered, and helps to redefine an era that changed every part of our lives.

    It brings together all the knowledge needed to write any program, use any standard or third-party Python 3 library, and create new library modules of your own.

    Indeed, that's what computers are for. You can enlist your own computer to automate all of your project's repetitive tasks, ranging from individual builds and running unit tests through to full product release, customer deployment, and monitoring the system.Many teams try to do these tasks by hand. That's usually a really bad idea: people just aren't as good at repetitive tasks as machines. You run the risk of doing it differently the one time it matters, on one machine but not another, or doing it just plain wrong. But the computer can do these tasks for you the same way, time after time, without bothering you. You can transform these labor-intensive, boring and potentially risky chores into automatic, background processes that just work.In this eagerly anticipated book, you'll find a variety of popular, open-source tools to help automate your project. With this book, you will learn: How to make your build processes accurate, reliable, fast, and easy. How to build complex systems at the touch of a button. How to build, test, and release software automatically, with no human intervention. Technologies and tools available for automation: which to use and when. Tricks and tips from the masters (do you know how to have your cell phone tell you that your build just failed?) You'll find easy-to-implement recipes to automate your Java project, using the same popular style as the rest of our Jolt Productivity Award-winning Starter Kit books. Armed with plenty of examples and concrete, pragmatic advice, you'll find it's easy to get started and reap the benefits of modern software development. You can begin to enjoy pragmatic, automatic, unattended software production that's reliable and accurate every time.